{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 基于自注意力机制的语言模型\n",
    "\n",
    "先做一个简单地拼音映射为汉字的实验。\n",
    "\n",
    "## 1. 数据处理\n",
    "- 读取数据"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "with open(\"data/zh.tsv\", 'r', encoding='utf-8') as fout:\n",
    "    data = fout.readlines()[:100]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|█████████████████████████████████████████████████████████████████████████████| 100/100 [00:00<00:00, 50129.13it/s]\n"
     ]
    }
   ],
   "source": [
    "from tqdm import tqdm\n",
    "\n",
    "inputs = []\n",
    "labels = []\n",
    "for i in tqdm(range(len(data))):\n",
    "    key, pny, hanzi = data[i].split('\\t')\n",
    "    inputs.append(pny.split(' '))\n",
    "    labels.append(hanzi.strip('\\n').split(' '))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[['lv4', 'shi4', 'yang2', 'chun1', 'yan1', 'jing3', 'da4', 'kuai4', 'wen2', 'zhang1', 'de', 'di3', 'se4', 'si4', 'yue4', 'de', 'lin2', 'luan2', 'geng4', 'shi4', 'lv4', 'de2', 'xian1', 'huo2', 'xiu4', 'mei4', 'shi1', 'yi4', 'ang4', 'ran2'], ['ta1', 'jin3', 'ping2', 'yao1', 'bu4', 'de', 'li4', 'liang4', 'zai4', 'yong3', 'dao4', 'shang4', 'xia4', 'fan1', 'teng2', 'yong3', 'dong4', 'she2', 'xing2', 'zhuang4', 'ru2', 'hai3', 'tun2', 'yi1', 'zhi2', 'yi3', 'yi1', 'tou2', 'de', 'you1', 'shi4', 'ling3', 'xian1'], ['pao4', 'yan3', 'da3', 'hao3', 'le', 'zha4', 'yao4', 'zen3', 'me', 'zhuang1', 'yue4', 'zheng4', 'cai2', 'yao3', 'le', 'yao3', 'ya2', 'shu1', 'de', 'tuo1', 'qu4', 'yi1', 'fu2', 'guang1', 'bang3', 'zi', 'chong1', 'jin4', 'le', 'shui3', 'cuan4', 'dong4'], ['ke3', 'shei2', 'zhi1', 'wen2', 'wan2', 'hou4', 'ta1', 'yi1', 'zhao4', 'jing4', 'zi', 'zhi3', 'jian4', 'zuo3', 'xia4', 'yan3', 'jian3', 'de', 'xian4', 'you4', 'cu1', 'you4', 'hei1', 'yu3', 'you4', 'ce4', 'ming2', 'xian3', 'bu4', 'dui4', 'cheng1'], ['qi1', 'shi2', 'nian2', 'dai4', 'mo4', 'wo3', 'wai4', 'chu1', 'qiu2', 'xue2', 'mu3', 'qin1', 'ding1', 'ning2', 'wo3', 'chi1', 'fan4', 'yao4', 'xi4', 'jue2', 'man4', 'yan4', 'xue2', 'xi2', 'yao4', 'shen1', 'zuan1', 'xi4', 'yan2']]\n",
      "\n",
      "[['绿', '是', '阳', '春', '烟', '景', '大', '块', '文', '章', '的', '底', '色', '四', '月', '的', '林', '峦', '更', '是', '绿', '得', '鲜', '活', '秀', '媚', '诗', '意', '盎', '然'], ['他', '仅', '凭', '腰', '部', '的', '力', '量', '在', '泳', '道', '上', '下', '翻', '腾', '蛹', '动', '蛇', '行', '状', '如', '海', '豚', '一', '直', '以', '一', '头', '的', '优', '势', '领', '先'], ['炮', '眼', '打', '好', '了', '炸', '药', '怎', '么', '装', '岳', '正', '才', '咬', '了', '咬', '牙', '倏', '地', '脱', '去', '衣', '服', '光', '膀', '子', '冲', '进', '了', '水', '窜', '洞'], ['可', '谁', '知', '纹', '完', '后', '她', '一', '照', '镜', '子', '只', '见', '左', '下', '眼', '睑', '的', '线', '又', '粗', '又', '黑', '与', '右', '侧', '明', '显', '不', '对', '称'], ['七', '十', '年', '代', '末', '我', '外', '出', '求', '学', '母', '亲', '叮', '咛', '我', '吃', '饭', '要', '细', '嚼', '慢', '咽', '学', '习', '要', '深', '钻', '细', '研']]\n"
     ]
    }
   ],
   "source": [
    "print(inputs[:5])\n",
    "print()\n",
    "print(labels[:5])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████████████████████████████████████████████████████████████████████████| 100/100 [00:00<00:00, 7712.39it/s]\n",
      "100%|██████████████████████████████████████████████████████████████████████████████| 100/100 [00:00<00:00, 5277.65it/s]\n"
     ]
    }
   ],
   "source": [
    "def get_vocab(data):\n",
    "    vocab = ['<PAD>']\n",
    "    for line in tqdm(data):\n",
    "        for char in line:\n",
    "            if char not in vocab:\n",
    "                vocab.append(char)\n",
    "    return vocab\n",
    "\n",
    "pny2id = get_vocab(inputs)\n",
    "han2id = get_vocab(labels)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['<PAD>', 'lv4', 'shi4', 'yang2', 'chun1', 'yan1', 'jing3', 'da4', 'kuai4', 'wen2']\n",
      "['<PAD>', '绿', '是', '阳', '春', '烟', '景', '大', '块', '文']\n"
     ]
    }
   ],
   "source": [
    "print(pny2id[:10])\n",
    "print(han2id[:10])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████████████████████████████████████████████████████████████████████████| 100/100 [00:00<00:00, 6591.81it/s]\n",
      "100%|██████████████████████████████████████████████████████████████████████████████| 100/100 [00:00<00:00, 3855.73it/s]\n"
     ]
    }
   ],
   "source": [
    "input_num = [[pny2id.index(pny) for pny in line] for line in tqdm(inputs)]\n",
    "label_num = [[han2id.index(han) for han in line] for line in tqdm(labels)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[  1   2   3   4   5   6   7   8   9  10  11  12  13  14  15  11  16  17\n",
      "   18   2   1  19  20  21  22  23  24  25  26  27   0   0   0]\n",
      " [ 28  29  30  31  32  11  33  34  35  36  37  38  39  40  41  36  42  43\n",
      "   44  45  46  47  48  49  50  51  49  52  11  53   2  54  20]\n",
      " [ 55  56  57  58  59  60  61  62  63  64  15  65  66  67  59  67  68  69\n",
      "   11  70  71  49  72  73  74  75  76  77  59  78  79  42   0]\n",
      " [ 80  81  82   9  83  84  28  49  85  86  75  87  88  89  39  56  90  11\n",
      "   91  92  93  92  94  95  92  96  97  98  32  99 100   0   0]]\n",
      "[[  1   2   3   4   5   6   7   8   9  10  11  12  13  14  15  11  16  17\n",
      "   18   2   1  19  20  21  22  23  24  25  26  27   0   0   0]\n",
      " [ 28  29  30  31  32  11  33  34  35  36  37  38  39  40  41  42  43  44\n",
      "   45  46  47  48  49  50  51  52  50  53  11  54  55  56  57]\n",
      " [ 58  59  60  61  62  63  64  65  66  67  68  69  70  71  62  71  72  73\n",
      "   74  75  76  77  78  79  80  81  82  83  62  84  85  86   0]\n",
      " [ 87  88  89  90  91  92  93  50  94  95  81  96  97  98  39  59  99  11\n",
      "  100 101 102 101 103 104 105 106 107 108 109 110 111   0   0]]\n"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "def get_batch(input_data, label_data, batch_size):\n",
    "    batch_num = len(input_data) // batch_size\n",
    "    for k in range(batch_num):\n",
    "        begin = k * batch_size\n",
    "        end = begin + batch_size\n",
    "        input_batch = input_data[begin:end]\n",
    "        label_batch = label_data[begin:end]\n",
    "        max_len = max([len(line) for line in input_batch])\n",
    "        input_batch = np.array([line + [0] * (max_len - len(line)) for line in input_batch])\n",
    "        label_batch = np.array([line + [0] * (max_len - len(line)) for line in label_batch])\n",
    "        yield input_batch, label_batch\n",
    "        \n",
    "        \n",
    "batch = get_batch(input_num, label_num, 4)\n",
    "input_batch, label_batch = next(batch)\n",
    "print(input_batch)\n",
    "print(label_batch)"
   ]
  },
  {
   "attachments": {
    "image.png": {
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"
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2.模型搭建\n",
    "模型采用self-attention,模型结构如下：\n",
    "\n",
    "![image.png](attachment:image.png)\n",
    "\n",
    "我们只需要搭建左侧编码器即可，不用搭建右侧解码器。\n",
    "\n",
    "论文地址：https://arxiv.org/abs/1706.03762\n",
    "\n",
    "模型代码搭建我们直接参考开源的代码：\n",
    "https://github.com/Kyubyong/transformer/blob/master/modules.py\n",
    "\n",
    "我们只需要注意每一快的输入输出数据形式怎样即可。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "import tensorflow as tf"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2.1 构造建模组件"
   ]
  },
  {
   "attachments": {
    "image.png": {
     "image/png": 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"
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "下面代码实现了图片结构中的各个功能组件。\n",
    "![image.png](attachment:image.png)\n",
    "\n",
    "#### layer norm层"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "def normalize(inputs, \n",
    "              epsilon = 1e-8,\n",
    "              scope=\"ln\",\n",
    "              reuse=None):\n",
    "    '''Applies layer normalization.\n",
    "\n",
    "    Args:\n",
    "      inputs: A tensor with 2 or more dimensions, where the first dimension has\n",
    "        `batch_size`.\n",
    "      epsilon: A floating number. A very small number for preventing ZeroDivision Error.\n",
    "      scope: Optional scope for `variable_scope`.\n",
    "      reuse: Boolean, whether to reuse the weights of a previous layer\n",
    "        by the same name.\n",
    "\n",
    "    Returns:\n",
    "      A tensor with the same shape and data dtype as `inputs`.\n",
    "    '''\n",
    "    with tf.variable_scope(scope, reuse=reuse):\n",
    "        inputs_shape = inputs.get_shape()\n",
    "        params_shape = inputs_shape[-1:]\n",
    "\n",
    "        mean, variance = tf.nn.moments(inputs, [-1], keep_dims=True)\n",
    "        beta= tf.Variable(tf.zeros(params_shape))\n",
    "        gamma = tf.Variable(tf.ones(params_shape))\n",
    "        normalized = (inputs - mean) / ( (variance + epsilon) ** (.5) )\n",
    "        outputs = gamma * normalized + beta\n",
    "\n",
    "    return outputs"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### embedding层"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "def embedding(inputs, \n",
    "              vocab_size, \n",
    "              num_units, \n",
    "              zero_pad=True, \n",
    "              scale=True,\n",
    "              scope=\"embedding\", \n",
    "              reuse=None):\n",
    "    '''Embeds a given tensor.\n",
    "    Args:\n",
    "      inputs: A `Tensor` with type `int32` or `int64` containing the ids\n",
    "         to be looked up in `lookup table`.\n",
    "      vocab_size: An int. Vocabulary size.\n",
    "      num_units: An int. Number of embedding hidden units.\n",
    "      zero_pad: A boolean. If True, all the values of the fist row (id 0)\n",
    "        should be constant zeros.\n",
    "      scale: A boolean. If True. the outputs is multiplied by sqrt num_units.\n",
    "      scope: Optional scope for `variable_scope`.\n",
    "      reuse: Boolean, whether to reuse the weights of a previous layer\n",
    "        by the same name.\n",
    "    Returns:\n",
    "      A `Tensor` with one more rank than inputs's. The last dimensionality\n",
    "        should be `num_units`.\n",
    "\n",
    "    For example,\n",
    "\n",
    "    ```\n",
    "    import tensorflow as tf\n",
    "\n",
    "    inputs = tf.to_int32(tf.reshape(tf.range(2*3), (2, 3)))\n",
    "    outputs = embedding(inputs, 6, 2, zero_pad=True)\n",
    "    with tf.Session() as sess:\n",
    "        sess.run(tf.global_variables_initializer())\n",
    "        print sess.run(outputs)\n",
    "    >>\n",
    "    [[[ 0.          0.        ]\n",
    "      [ 0.09754146  0.67385566]\n",
    "      [ 0.37864095 -0.35689294]]\n",
    "     [[-1.01329422 -1.09939694]\n",
    "      [ 0.7521342   0.38203377]\n",
    "      [-0.04973143 -0.06210355]]]\n",
    "    ```\n",
    "\n",
    "    ```\n",
    "    import tensorflow as tf\n",
    "\n",
    "    inputs = tf.to_int32(tf.reshape(tf.range(2*3), (2, 3)))\n",
    "    outputs = embedding(inputs, 6, 2, zero_pad=False)\n",
    "    with tf.Session() as sess:\n",
    "        sess.run(tf.global_variables_initializer())\n",
    "        print sess.run(outputs)\n",
    "    >>\n",
    "    [[[-0.19172323 -0.39159766]\n",
    "      [-0.43212751 -0.66207761]\n",
    "      [ 1.03452027 -0.26704335]]\n",
    "     [[-0.11634696 -0.35983452]\n",
    "      [ 0.50208133  0.53509563]\n",
    "      [ 1.22204471 -0.96587461]]]\n",
    "    ```    \n",
    "    '''\n",
    "    with tf.variable_scope(scope, reuse=reuse):\n",
    "        lookup_table = tf.get_variable('lookup_table',\n",
    "                                       dtype=tf.float32,\n",
    "                                       shape=[vocab_size, num_units],\n",
    "                                       initializer=tf.contrib.layers.xavier_initializer())\n",
    "        if zero_pad:\n",
    "            lookup_table = tf.concat((tf.zeros(shape=[1, num_units]),\n",
    "                                      lookup_table[1:, :]), 0)\n",
    "        outputs = tf.nn.embedding_lookup(lookup_table, inputs)\n",
    "\n",
    "        if scale:\n",
    "            outputs = outputs * (num_units ** 0.5) \n",
    "\n",
    "    return outputs"
   ]
  },
  {
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"
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### multihead层\n",
    "该层实现了下面功能：\n",
    "![image.png](attachment:image.png)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "def multihead_attention(emb,\n",
    "                        queries, \n",
    "                        keys, \n",
    "                        num_units=None, \n",
    "                        num_heads=8, \n",
    "                        dropout_rate=0,\n",
    "                        is_training=True,\n",
    "                        causality=False,\n",
    "                        scope=\"multihead_attention\", \n",
    "                        reuse=None):\n",
    "    '''Applies multihead attention.\n",
    "    \n",
    "    Args:\n",
    "      queries: A 3d tensor with shape of [N, T_q, C_q].\n",
    "      keys: A 3d tensor with shape of [N, T_k, C_k].\n",
    "      num_units: A scalar. Attention size.\n",
    "      dropout_rate: A floating point number.\n",
    "      is_training: Boolean. Controller of mechanism for dropout.\n",
    "      causality: Boolean. If true, units that reference the future are masked. \n",
    "      num_heads: An int. Number of heads.\n",
    "      scope: Optional scope for `variable_scope`.\n",
    "      reuse: Boolean, whether to reuse the weights of a previous layer\n",
    "        by the same name.\n",
    "        \n",
    "    Returns\n",
    "      A 3d tensor with shape of (N, T_q, C)  \n",
    "    '''\n",
    "    with tf.variable_scope(scope, reuse=reuse):\n",
    "        # Set the fall back option for num_units\n",
    "        if num_units is None:\n",
    "            num_units = queries.get_shape().as_list[-1]\n",
    "        \n",
    "        # Linear projections\n",
    "        Q = tf.layers.dense(queries, num_units, activation=tf.nn.relu) # (N, T_q, C)\n",
    "        K = tf.layers.dense(keys, num_units, activation=tf.nn.relu) # (N, T_k, C)\n",
    "        V = tf.layers.dense(keys, num_units, activation=tf.nn.relu) # (N, T_k, C)\n",
    "        \n",
    "        # Split and concat\n",
    "        Q_ = tf.concat(tf.split(Q, num_heads, axis=2), axis=0) # (h*N, T_q, C/h) \n",
    "        K_ = tf.concat(tf.split(K, num_heads, axis=2), axis=0) # (h*N, T_k, C/h) \n",
    "        V_ = tf.concat(tf.split(V, num_heads, axis=2), axis=0) # (h*N, T_k, C/h) \n",
    "\n",
    "        # Multiplication\n",
    "        outputs = tf.matmul(Q_, tf.transpose(K_, [0, 2, 1])) # (h*N, T_q, T_k)\n",
    "        \n",
    "        # Scale\n",
    "        outputs = outputs / (K_.get_shape().as_list()[-1] ** 0.5)\n",
    "        \n",
    "        # Key Masking\n",
    "        key_masks = tf.sign(tf.abs(tf.reduce_sum(emb, axis=-1))) # (N, T_k)\n",
    "        key_masks = tf.tile(key_masks, [num_heads, 1]) # (h*N, T_k)\n",
    "        key_masks = tf.tile(tf.expand_dims(key_masks, 1), [1, tf.shape(queries)[1], 1]) # (h*N, T_q, T_k)\n",
    "        \n",
    "        paddings = tf.ones_like(outputs)*(-2**32+1)\n",
    "        outputs = tf.where(tf.equal(key_masks, 0), paddings, outputs) # (h*N, T_q, T_k)\n",
    "  \n",
    "        # Causality = Future blinding\n",
    "        if causality:\n",
    "            diag_vals = tf.ones_like(outputs[0, :, :]) # (T_q, T_k)\n",
    "            tril = tf.contrib.linalg.LinearOperatorTriL(diag_vals).to_dense() # (T_q, T_k)\n",
    "            masks = tf.tile(tf.expand_dims(tril, 0), [tf.shape(outputs)[0], 1, 1]) # (h*N, T_q, T_k)\n",
    "   \n",
    "            paddings = tf.ones_like(masks)*(-2**32+1)\n",
    "            outputs = tf.where(tf.equal(masks, 0), paddings, outputs) # (h*N, T_q, T_k)\n",
    "  \n",
    "        # Activation\n",
    "        outputs = tf.nn.softmax(outputs) # (h*N, T_q, T_k)\n",
    "         \n",
    "        # Query Masking\n",
    "        query_masks = tf.sign(tf.abs(tf.reduce_sum(emb, axis=-1))) # (N, T_q)\n",
    "        query_masks = tf.tile(query_masks, [num_heads, 1]) # (h*N, T_q)\n",
    "        query_masks = tf.tile(tf.expand_dims(query_masks, -1), [1, 1, tf.shape(keys)[1]]) # (h*N, T_q, T_k)\n",
    "        outputs *= query_masks # broadcasting. (N, T_q, C)\n",
    "          \n",
    "        # Dropouts\n",
    "        outputs = tf.layers.dropout(outputs, rate=dropout_rate, training=tf.convert_to_tensor(is_training))\n",
    "               \n",
    "        # Weighted sum\n",
    "        outputs = tf.matmul(outputs, V_) # ( h*N, T_q, C/h)\n",
    "        \n",
    "        # Restore shape\n",
    "        outputs = tf.concat(tf.split(outputs, num_heads, axis=0), axis=2 ) # (N, T_q, C)\n",
    "              \n",
    "        # Residual connection\n",
    "        outputs += queries\n",
    "              \n",
    "        # Normalize\n",
    "        outputs = normalize(outputs) # (N, T_q, C)\n",
    " \n",
    "    return outputs"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### feedforward\n",
    "\n",
    "两层全连接，用卷积模拟加速运算，也可以使用dense层。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "def feedforward(inputs, \n",
    "                num_units=[2048, 512],\n",
    "                scope=\"multihead_attention\", \n",
    "                reuse=None):\n",
    "    '''Point-wise feed forward net.\n",
    "    \n",
    "    Args:\n",
    "      inputs: A 3d tensor with shape of [N, T, C].\n",
    "      num_units: A list of two integers.\n",
    "      scope: Optional scope for `variable_scope`.\n",
    "      reuse: Boolean, whether to reuse the weights of a previous layer\n",
    "        by the same name.\n",
    "        \n",
    "    Returns:\n",
    "      A 3d tensor with the same shape and dtype as inputs\n",
    "    '''\n",
    "    with tf.variable_scope(scope, reuse=reuse):\n",
    "        # Inner layer\n",
    "        params = {\"inputs\": inputs, \"filters\": num_units[0], \"kernel_size\": 1,\n",
    "                  \"activation\": tf.nn.relu, \"use_bias\": True}\n",
    "        outputs = tf.layers.conv1d(**params)\n",
    "        \n",
    "        # Readout layer\n",
    "        params = {\"inputs\": outputs, \"filters\": num_units[1], \"kernel_size\": 1,\n",
    "                  \"activation\": None, \"use_bias\": True}\n",
    "        outputs = tf.layers.conv1d(**params)\n",
    "        \n",
    "        # Residual connection\n",
    "        outputs += inputs\n",
    "        \n",
    "        # Normalize\n",
    "        outputs = normalize(outputs)\n",
    "    \n",
    "    return outputs"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### label_smoothing.\n",
    "对于训练有好处，将0变为接近零的小数，1变为接近1的数，原文：\n",
    "\n",
    "During training, we employed label smoothing of value \u000fls = 0.1 [36]. This hurts perplexity, as the model learns to be more unsure, but improves accuracy and BLEU score."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "def label_smoothing(inputs, epsilon=0.1):\n",
    "    '''Applies label smoothing. See https://arxiv.org/abs/1512.00567.\n",
    "    \n",
    "    Args:\n",
    "      inputs: A 3d tensor with shape of [N, T, V], where V is the number of vocabulary.\n",
    "      epsilon: Smoothing rate.\n",
    "    \n",
    "    For example,\n",
    "    \n",
    "    ```\n",
    "    import tensorflow as tf\n",
    "    inputs = tf.convert_to_tensor([[[0, 0, 1], \n",
    "       [0, 1, 0],\n",
    "       [1, 0, 0]],\n",
    "      [[1, 0, 0],\n",
    "       [1, 0, 0],\n",
    "       [0, 1, 0]]], tf.float32)\n",
    "       \n",
    "    outputs = label_smoothing(inputs)\n",
    "    \n",
    "    with tf.Session() as sess:\n",
    "        print(sess.run([outputs]))\n",
    "    \n",
    "    >>\n",
    "    [array([[[ 0.03333334,  0.03333334,  0.93333334],\n",
    "        [ 0.03333334,  0.93333334,  0.03333334],\n",
    "        [ 0.93333334,  0.03333334,  0.03333334]],\n",
    "       [[ 0.93333334,  0.03333334,  0.03333334],\n",
    "        [ 0.93333334,  0.03333334,  0.03333334],\n",
    "        [ 0.03333334,  0.93333334,  0.03333334]]], dtype=float32)]   \n",
    "    ```    \n",
    "    '''\n",
    "    K = inputs.get_shape().as_list()[-1] # number of channels\n",
    "    return ((1-epsilon) * inputs) + (epsilon / K)"
   ]
  },
  {
   "attachments": {
    "image.png": {
     "image/png": 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"
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2.2 搭建模型\n",
    "模型实现下图结构：\n",
    "![image.png](attachment:image.png)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "class Graph():\n",
    "    def __init__(self, is_training=True):\n",
    "        tf.reset_default_graph()\n",
    "        self.is_training = arg.is_training\n",
    "        self.hidden_units = arg.hidden_units\n",
    "        self.input_vocab_size = arg.input_vocab_size\n",
    "        self.label_vocab_size = arg.label_vocab_size\n",
    "        self.num_heads = arg.num_heads\n",
    "        self.num_blocks = arg.num_blocks\n",
    "        self.max_length = arg.max_length\n",
    "        self.lr = arg.lr\n",
    "        self.dropout_rate = arg.dropout_rate\n",
    "        \n",
    "        # input\n",
    "        self.x = tf.placeholder(tf.int32, shape=(None, None))\n",
    "        self.y = tf.placeholder(tf.int32, shape=(None, None))\n",
    "        # embedding\n",
    "        self.emb = embedding(self.x, vocab_size=self.input_vocab_size, num_units=self.hidden_units, scale=True, scope=\"enc_embed\")\n",
    "        self.enc = self.emb + embedding(tf.tile(tf.expand_dims(tf.range(tf.shape(self.x)[1]), 0), [tf.shape(self.x)[0], 1]),\n",
    "                                      vocab_size=self.max_length,num_units=self.hidden_units, zero_pad=False, scale=False,scope=\"enc_pe\")\n",
    "        ## Dropout\n",
    "        self.enc = tf.layers.dropout(self.enc, \n",
    "                                    rate=self.dropout_rate, \n",
    "                                    training=tf.convert_to_tensor(self.is_training))\n",
    "                \n",
    "        ## Blocks\n",
    "        for i in range(self.num_blocks):\n",
    "            with tf.variable_scope(\"num_blocks_{}\".format(i)):\n",
    "                ### Multihead Attention\n",
    "                self.enc = multihead_attention(emb = self.emb,\n",
    "                                               queries=self.enc, \n",
    "                                                keys=self.enc, \n",
    "                                                num_units=self.hidden_units, \n",
    "                                                num_heads=self.num_heads, \n",
    "                                                dropout_rate=self.dropout_rate,\n",
    "                                                is_training=self.is_training,\n",
    "                                                causality=False)\n",
    "                        \n",
    "        ### Feed Forward\n",
    "        self.outputs = feedforward(self.enc, num_units=[4*self.hidden_units, self.hidden_units])\n",
    "            \n",
    "                \n",
    "        # Final linear projection\n",
    "        self.logits = tf.layers.dense(self.outputs, self.label_vocab_size)\n",
    "        self.preds = tf.to_int32(tf.argmax(self.logits, axis=-1))\n",
    "        self.istarget = tf.to_float(tf.not_equal(self.y, 0))\n",
    "        self.acc = tf.reduce_sum(tf.to_float(tf.equal(self.preds, self.y))*self.istarget)/ (tf.reduce_sum(self.istarget))\n",
    "        tf.summary.scalar('acc', self.acc)\n",
    "                \n",
    "        if is_training:  \n",
    "            # Loss\n",
    "            self.y_smoothed = label_smoothing(tf.one_hot(self.y, depth=self.label_vocab_size))\n",
    "            self.loss = tf.nn.softmax_cross_entropy_with_logits(logits=self.logits, labels=self.y_smoothed)\n",
    "            self.mean_loss = tf.reduce_sum(self.loss*self.istarget) / (tf.reduce_sum(self.istarget))\n",
    "               \n",
    "            # Training Scheme\n",
    "            self.global_step = tf.Variable(0, name='global_step', trainable=False)\n",
    "            self.optimizer = tf.train.AdamOptimizer(learning_rate=self.lr, beta1=0.9, beta2=0.98, epsilon=1e-8)\n",
    "            self.train_op = self.optimizer.minimize(self.mean_loss, global_step=self.global_step)\n",
    "                   \n",
    "            # Summary \n",
    "            tf.summary.scalar('mean_loss', self.mean_loss)\n",
    "            self.merged = tf.summary.merge_all()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 3. 训练模型\n",
    "### 3.1 参数设定"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "def create_hparams():\n",
    "    params = tf.contrib.training.HParams(\n",
    "        num_heads = 8,\n",
    "        num_blocks = 6,\n",
    "        # vocab\n",
    "        input_vocab_size = 50,\n",
    "        label_vocab_size = 50,\n",
    "        # embedding size\n",
    "        max_length = 100,\n",
    "        hidden_units = 512,\n",
    "        dropout_rate = 0.2,\n",
    "        lr = 0.0003,\n",
    "        is_training = True)\n",
    "    return params\n",
    "\n",
    "        \n",
    "arg = create_hparams()\n",
    "arg.input_vocab_size = len(pny2id)\n",
    "arg.label_vocab_size = len(han2id)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 3.2 模型训练"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "WARNING:tensorflow:From d:\\ProgramData\\Anaconda3\\lib\\site-packages\\tensorflow\\python\\util\\deprecation.py:497: calling conv1d (from tensorflow.python.ops.nn_ops) with data_format=NHWC is deprecated and will be removed in a future version.\n",
      "Instructions for updating:\n",
      "`NHWC` for data_format is deprecated, use `NWC` instead\n",
      "WARNING:tensorflow:From <ipython-input-14-862b249aa009>:53: softmax_cross_entropy_with_logits (from tensorflow.python.ops.nn_ops) is deprecated and will be removed in a future version.\n",
      "Instructions for updating:\n",
      "\n",
      "Future major versions of TensorFlow will allow gradients to flow\n",
      "into the labels input on backprop by default.\n",
      "\n",
      "See tf.nn.softmax_cross_entropy_with_logits_v2.\n",
      "\n",
      "epochs 5 : average loss =  1.6399681091308593\n",
      "epochs 10 : average loss =  1.1646613264083863\n",
      "epochs 15 : average loss =  1.157580156326294\n",
      "epochs 20 : average loss =  1.1407248640060426\n",
      "epochs 25 : average loss =  1.1298853492736816\n"
     ]
    }
   ],
   "source": [
    "import os\n",
    "\n",
    "epochs = 25\n",
    "batch_size = 4\n",
    "\n",
    "g = Graph(arg)\n",
    "\n",
    "saver =tf.train.Saver()\n",
    "with tf.Session() as sess:\n",
    "    merged = tf.summary.merge_all()\n",
    "    sess.run(tf.global_variables_initializer())\n",
    "    if os.path.exists('logs/model.meta'):\n",
    "        saver.restore(sess, 'logs/model')\n",
    "    writer = tf.summary.FileWriter('tensorboard/lm', tf.get_default_graph())\n",
    "    for k in range(epochs):\n",
    "        total_loss = 0\n",
    "        batch_num = len(input_num) // batch_size\n",
    "        batch = get_batch(input_num, label_num, batch_size)\n",
    "        for i in range(batch_num):\n",
    "            input_batch, label_batch = next(batch)\n",
    "            feed = {g.x: input_batch, g.y: label_batch}\n",
    "            cost,_ = sess.run([g.mean_loss,g.train_op], feed_dict=feed)\n",
    "            total_loss += cost\n",
    "            if (k * batch_num + i) % 10 == 0:\n",
    "                rs=sess.run(merged, feed_dict=feed)\n",
    "                writer.add_summary(rs, k * batch_num + i)\n",
    "        if (k+1) % 5 == 0:\n",
    "            print('epochs', k+1, ': average loss = ', total_loss/batch_num)\n",
    "    saver.save(sess, 'logs/model')\n",
    "    writer.close()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 3.3 模型推断"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Restoring parameters from logs/model\n",
      "输入测试拼音: shen1 ye4 shi2 er4 dian3 zhong1 ta1 zhan4 zai4 shao4 wei4 shang4 huan2 shi4 zhou1 wei2 yin1 sen1 ke3 bu4 yue4 xiang3 yue4 hai4 pa4 bao4 qiang1 ku1 zhe pao3 hui2 ying2 fang2\n",
      "深夜十二点钟他站在哨位上环视周围阴森可怖越想越害怕抱枪哭着跑回营房\n",
      "输入测试拼音: wu3 yue4 er4 shi2 jiu3 ri4 ye4 wan3 ao4 da4 li4 ya4 shou3 dou1 kan1 pei2 la1 de huang2 jia1 ju4 yuan4 re4 lie4 er2 chong1 man3 zhe zhen1 qing2\n",
      "五月二十九日夜晚澳大利亚首都堪培拉的皇家剧院热烈而充满着真情\n",
      "输入测试拼音: tai4 hu2 dong1 an4 yi1 dai4 de yun2 tuan2 you2 dan4 dao4 nong2 zai4 you2 nong2 dao4 dan4 er2 shang4 hai3 shi4 qu1 shang4 kong1 de yun2 yue4 lai2 yue4 shao3 yue4 lai2 yue4 xi1\n",
      "太湖东岸一带的云团由淡到浓再由浓到淡而上海市区上空的云越来越少越来越稀\n",
      "输入测试拼音: exit\n"
     ]
    }
   ],
   "source": [
    "arg.is_training = False\n",
    "\n",
    "g = Graph(arg)\n",
    "\n",
    "saver =tf.train.Saver()\n",
    "\n",
    "with tf.Session() as sess:\n",
    "    saver.restore(sess, 'logs/model')\n",
    "    while True:\n",
    "        line = input('输入测试拼音: ')\n",
    "        if line == 'exit': break\n",
    "        line = line.strip('\\n').split(' ')\n",
    "        x = np.array([pny2id.index(pny) for pny in line])\n",
    "        x = x.reshape(1, -1)\n",
    "        preds = sess.run(g.preds, {g.x: x})\n",
    "        got = ''.join(han2id[idx] for idx in preds[0])\n",
    "        print(got)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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